Моделі ризику смертності на основі дерева рішень і ансаблю для госпіталізованих пацієнтів із COVID-19
The work is devoted to studying SARS-CoV-2-associated pneumonia and the investigating of the main indicators that lead to the patients’ mortality. Using the good-known parameters that are routinely embraced in clinical practice, we obtained new functional dependencies based on an accessible and unde...
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| Видавець: | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
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| Дата: | 2023 |
| Автори: | , , , , , , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2023
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| Теми: | |
| Онлайн доступ: | http://journal.iasa.kpi.ua/article/view/279747 |
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Організація
System research and information technologies| Резюме: | The work is devoted to studying SARS-CoV-2-associated pneumonia and the investigating of the main indicators that lead to the patients’ mortality. Using the good-known parameters that are routinely embraced in clinical practice, we obtained new functional dependencies based on an accessible and understandable decision tree and ML ensemble of classifiers models that would allow the physician to determine the prognosis in a few minutes and, accordingly, to understand the need for treatment adjustment, transfer of the patient to the emergency department. The accuracy of the resulting ensemble of models fitted on actual hospital patient data was in the range of 0.88–0.91 for different metrics. Creating a data collection system with further training of classifiers will dynamically increase the forecast’s accuracy and automate the doctor’s decision-making process. |
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